CN114565435A - Customer intelligent management platform based on big data analysis technology - Google Patents

Customer intelligent management platform based on big data analysis technology Download PDF

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Publication number
CN114565435A
CN114565435A CN202210188369.4A CN202210188369A CN114565435A CN 114565435 A CN114565435 A CN 114565435A CN 202210188369 A CN202210188369 A CN 202210188369A CN 114565435 A CN114565435 A CN 114565435A
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data
client
determining
module
scene
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萧毅
杨建全
王旭中
潘建东
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Color Technology Shenzhen Co ltd
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Color Technology Shenzhen Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0633—Lists, e.g. purchase orders, compilation or processing
    • G06Q30/0635—Processing of requisition or of purchase orders
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/602—Providing cryptographic facilities or services
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0631—Item recommendations

Abstract

The invention discloses a customer intelligent management platform based on big data analysis technology, comprising: the acquisition module is used for acquiring the login information of the client and carrying out verification processing: the first determining module is used for checking the valid duration voucher of the client when the validation passes, and determining the login state of the client according to the expiration time of the valid duration voucher; the establishing module is used for acquiring the business data of the client in the login process and marking the industry type of the client; collecting a target data source according to the industry type of a client, and establishing a big data directory according to the target data source; the matching module is used for matching the service data with the big data directory to determine matching data; and the second determining module is used for determining the associated data related to the matching data in the big data directory and pushing the associated data to the client. And the associated data is accurately recommended to the client, so that the client experience is improved.

Description

Customer intelligent management platform based on big data analysis technology
Technical Field
The invention relates to the technical field of big data, in particular to a customer intelligent management platform based on big data analysis technology.
Background
Currently, big data analysis refers to the analysis of data of huge scale. With the advent of the big data age, big data analysis also arose. The client intelligent management platform in the prior art cannot accurately verify the login information and the login state of the client, and cannot determine recommended data based on big data according to specific data of the client.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the art described above. Therefore, the invention aims to provide a customer intelligent management platform based on a big data analysis technology, which can accurately verify the login information and the login state of a customer, accurately determine recommended data based on big data according to specific data of the customer and improve customer experience.
In order to achieve the above object, an embodiment of the present invention provides a customer intelligent management platform based on big data analysis technology, including:
the acquisition module is used for acquiring the login information of the client and carrying out verification processing:
the first determining module is used for checking the valid duration voucher of the client when the validation passes, and determining the login state of the client according to the expiration time of the valid duration voucher;
the establishing module is used for acquiring the business data of the client in the login process and marking the industry type of the client; collecting a target data source according to the industry type of a client, and establishing a big data directory according to the target data source;
the matching module is used for matching the service data with the big data directory to determine matching data;
and the second determining module is used for determining the associated data related to the matched data in the big data directory and pushing the associated data to the client.
According to some embodiments of the invention, the login information comprises a username and a user password.
According to some embodiments of the invention, further comprising a building block for
Acquiring historical application data of a client;
performing data analysis on the historical application data, determining scene data and content data, dividing the scene data based on a preset scene category, and determining the scene data into a plurality of scene nodes;
acquiring the node levels of the scene nodes, and determining the connection relation among the scene nodes according to the node levels;
filling the content data to corresponding scene nodes, and constructing a scene tree according to the connection relation;
extracting the characteristics of content data in each scene node in the scene tree, and determining client labels in different scenes;
and respectively constructing customer images of different scenes according to the customer labels in the different scenes.
According to some embodiments of the invention, further comprising: detection module for
Acquiring current application data of a client;
analyzing the current application data, and determining a current scene and current content;
extracting the characteristics of the current content, and determining a temporary label in the current scene;
constructing a temporary customer portrait of the current scene according to the temporary label;
calculating the matching degree of the temporary customer portrait and the customer portrait corresponding to the current scene, and judging whether the matching degree is greater than a preset matching degree;
when the matching degree is smaller than a preset matching degree, analyzing the current content, determining a client behavior, and decomposing the client behavior into a plurality of sub-behaviors;
establishing a queuing queue according to the plurality of sub-behaviors, and determining every two adjacent sub-behaviors in the queuing queue as a group as a detection group;
respectively calculating the association degrees between two sub-behaviors in the detection group, and screening out the detection group with the association degree smaller than the preset association degree as a marker group;
respectively judging whether the two sub-behaviors in the mark group are complete behaviors, and sending an alarm prompt when the mark group with the two sub-behaviors which are not complete behaviors is determined to exist;
otherwise, the client portrait corresponding to the current scene is updated according to the temporary client portrait.
According to some embodiments of the invention, further comprising: shared module for
Receiving data request information of a first client and sending the data request information to a second client;
receiving feedback information of a second client, and establishing a data sharing channel between the first client and the second client according to the feedback information;
and sending request data corresponding to the data request information to the first client based on the data sharing channel.
According to some embodiments of the invention, further comprising: and the encryption module is used for encrypting the request data corresponding to the data request information before sending the request data to the first client based on the data sharing channel.
According to some embodiments of the invention, further comprising a prediction module for
Detecting whether an attack event exists or not in the process of sending request data by the sharing module;
when an attack event is determined to occur, determining an attack sequence diagram;
inputting the attack sequence diagram into a pre-trained prediction model to determine prediction information;
and determining a protective measure for the attack node according to the prediction information.
According to some embodiments of the invention, further comprising:
setting a main client, wherein the main client comprises a plurality of data sharing channels;
detecting the access amount of the main client in a preset time period, and judging whether the access amount is greater than a preset threshold value;
and when the access amount is determined to be larger than the preset threshold value, extracting the access behavior characteristics of the access main client, matching the access behavior characteristics with the abnormal access behavior characteristics, and determining whether the access behavior characteristics of the access main client are the abnormal access behavior characteristics or not according to the matching result.
According to some embodiments of the invention, further comprising: a third determination module for
After receiving the request data, the second client converts the request data into a target text and performs word segmentation to obtain a word segmentation set;
carrying out numerical processing on each participle in the participle set to determine an analytic numerical sequence;
determining a target number sequence of the request data before transmission;
and comparing the target digital sequence with the analysis numerical sequence, and determining abnormal information according to the comparison result.
According to some embodiments of the invention, further comprising:
the supplier module is used for receiving the associated data and screening out a target supplier according to the associated data;
a quotation module to:
receiving quotation information sent by the target supplier, carrying out comprehensive analysis on the quotation information to obtain an analysis result, generating a new quotation according to the analysis result and sending the new quotation to a client;
and receiving confirmation information of the customer on the new price report, and generating order information according to the confirmation information. Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a block diagram of a customer intelligent management platform based on big data analytics technology, according to one embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
As shown in fig. 1, an embodiment of the present invention provides a customer intelligent management platform based on big data analysis technology, including:
the acquisition module is used for acquiring the login information of the client and carrying out verification processing:
the first determining module is used for checking the valid duration voucher of the client when the validation passes, and determining the login state of the client according to the expiration time of the valid duration voucher;
the establishing module is used for acquiring the business data of the client in the login process and marking the industry type of the client; collecting a target data source according to the industry type of a client, and establishing a big data directory according to the target data source;
the matching module is used for matching the service data with the big data directory to determine matching data;
and the second determining module is used for determining the associated data related to the matched data in the big data directory and pushing the associated data to the client.
The working principle of the technical scheme is as follows: the acquisition module is used for acquiring the login information of the client and carrying out verification processing: and the login information of the client is accurately verified. The first determining module is used for checking the valid duration voucher of the client when the validation passes, and determining the login state of the client according to the expiration time of the valid duration voucher; and determining when the client logs out according to the expiration time of the effective duration voucher, so that the access to the client is based on the effective duration voucher, the control on the login information is improved, and the safety is improved. The establishing module is used for acquiring the business data of the client in the login process and marking the industry type of the client; collecting a target data source according to the industry type of a client, and establishing a big data directory according to the target data source; the matching module is used for matching the service data with the big data directory to determine matching data; and the second determining module is used for determining the associated data related to the matched data in the big data directory and pushing the associated data to the client.
The beneficial effects of the above technical scheme are that: the login information and the login state of the client are accurately verified, the big data directory of the same industry is determined according to the industry type of the client, the matching data is determined according to the matching between the business data and the big data directory, the associated data is further determined, more accurate data can be conveniently recommended for the client, and the client experience is improved.
According to some embodiments of the invention, the login information comprises a user name and a user password.
According to some embodiments of the invention, further comprising a building block for
Acquiring historical application data of a client;
performing data analysis on the historical application data, determining scene data and content data, dividing the scene data based on a preset scene category, and determining the scene data into a plurality of scene nodes;
acquiring the node levels of the scene nodes, and determining the connection relation among the scene nodes according to the node levels;
filling the content data to corresponding scene nodes, and constructing a scene tree according to the connection relation;
extracting the characteristics of the content data in each scene node in the scene tree, and determining client labels in different scenes;
and respectively constructing customer images of different scenes according to the customer labels in the different scenes.
The working principle of the technical scheme is as follows: the system also comprises a construction module used for acquiring the historical application data of the client; performing data analysis on the historical application data, determining scene data and content data, dividing the scene data based on a preset scene category, and determining the scene data into a plurality of scene nodes; acquiring the node levels of the scene nodes, and determining the connection relation among the scene nodes according to the node levels; filling the content data to corresponding scene nodes, and constructing a scene tree according to the connection relation; extracting the characteristics of the content data in each scene node in the scene tree, and determining client labels in different scenes; and respectively constructing customer images of different scenes according to the customer labels in the different scenes.
The beneficial effects of the above technical scheme are that: the client portrait of different scenes is constructed respectively according to the client tags in different scenes, the efficiency and the accuracy of determining the client portrait are improved, the inaccuracy of determining the client portrait without considering the scenes of the clients in the prior art is avoided, the client portrait is stored, intelligent management of the clients is facilitated according to the client portrait, and the behavior characteristics of the clients are determined.
According to some embodiments of the invention, further comprising: detection module for
Acquiring current application data of a client;
analyzing the current application data, and determining a current scene and current content;
extracting the characteristics of the current content, and determining a temporary label in the current scene;
constructing a temporary customer portrait of the current scene according to the temporary label;
calculating the matching degree of the temporary customer portrait and the customer portrait corresponding to the current scene, and judging whether the matching degree is greater than a preset matching degree;
when the matching degree is smaller than a preset matching degree, analyzing the current content, determining a client behavior, and decomposing the client behavior into a plurality of sub-behaviors;
establishing a queuing queue according to the plurality of sub-behaviors, and determining every two adjacent sub-behaviors in the queuing queue as a group as a detection group;
respectively calculating the association degree between two child behaviors in the detection group, and screening out the detection group with the association degree smaller than the preset association degree as a marker group;
respectively judging whether the two sub-behaviors in the mark group are complete behaviors, and sending an alarm prompt when the mark group with the two sub-behaviors which are not complete behaviors is determined to exist;
otherwise, the client portrait corresponding to the current scene is updated according to the temporary client portrait.
The working principle of the technical scheme is as follows: acquiring current application data of a client; analyzing the current application data, and determining a current scene and current content; extracting the characteristics of the current content, and determining a temporary label in the current scene; constructing a temporary customer portrait of the current scene according to the temporary label; calculating the matching degree of the temporary customer portrait and the customer portrait corresponding to the current scene, and judging whether the matching degree is greater than a preset matching degree; when the matching degree is smaller than a preset matching degree, analyzing the current content, determining a customer behavior, and decomposing the customer behavior into a plurality of sub behaviors; establishing a queuing queue according to the plurality of sub-behaviors, and determining every two adjacent sub-behaviors in the queuing queue as a group as a detection group; respectively calculating the association degrees between two sub-behaviors in the detection group, and screening out the detection group with the association degree smaller than the preset association degree as a marker group; respectively judging whether the two sub-behaviors in the mark group are complete behaviors, and sending an alarm prompt when the mark group with the two sub-behaviors which are not complete behaviors is determined to exist; otherwise, the client portrait corresponding to the current scene is updated according to the temporary client portrait. The complete behavior represents an independent behavior, i.e., the child behavior A and the child behavior B are grouped into a tag. A as one job and B as the other. The degree of association of a with B is not high.
The beneficial effects of the above technical scheme are that: and detecting the current application data, determining the abnormal behavior of the client according to the detection result, and sending an alarm prompt, so as to further determine the identity of the client. When the identity of the client is determined to be legal, the client portrait corresponding to the current scene is updated according to the temporary client portrait, so that the accuracy of the stored client portrait is ensured, and the client is managed accurately.
According to some embodiments of the invention, further comprising: shared module for
Receiving data request information of a first client and sending the data request information to a second client;
receiving feedback information of a second client, and establishing a data sharing channel between the first client and the second client according to the feedback information;
and sending request data corresponding to the data request information to the first client based on the data sharing channel.
The working principle of the technical scheme is as follows: the sharing module is used for receiving the data request information of the first client and sending the data request information to the second client; receiving feedback information of a second client, and establishing a data sharing channel between the first client and the second client according to the feedback information; and sending request data corresponding to the data request information to the first client based on the data sharing channel.
The beneficial effects of the above technical scheme are that: the data sharing management among the clients is realized, the data isolated island is eliminated, the data sharing duration is shortened based on the data sharing channel, and the data sharing efficiency is improved.
According to some embodiments of the invention, further comprising: and the encryption module is used for encrypting the request data corresponding to the data request information before sending the request data to the first client based on the data sharing channel.
The working principle of the technical scheme is as follows: and the encryption module is used for encrypting the request data corresponding to the data request information before sending the request data to the first client based on the data sharing channel.
The beneficial effects of the above technical scheme are that: the security of the request data during transmission is improved, and data leakage is avoided.
According to some embodiments of the invention, further comprising a prediction module for
Detecting whether an attack event exists or not in the process of sending request data by the sharing module;
when an attack event is determined to occur, determining an attack sequence diagram;
inputting the attack sequence diagram into a pre-trained prediction model to determine prediction information;
and determining a protective measure for the attack node according to the prediction information.
The working principle of the technical scheme is as follows: the system also comprises a prediction module used for detecting whether an attack event exists or not in the process of sending the request data by the sharing module; when an attack event is determined to occur, determining an attack sequence diagram; inputting the attack sequence diagram into a pre-trained prediction model to determine prediction information; and determining a protective measure for the attack node according to the prediction information.
The beneficial effects of the above technical scheme are that: whether the attack event exists in the request data in the sending process is conveniently and accurately determined, the attack event is determined to exist, prediction is carried out in time, the attack node is protected, the influence of the attack event is reduced, and the security of the request data transmission is improved.
According to some embodiments of the invention, further comprising:
setting a main client, wherein the main client comprises a plurality of data sharing channels;
detecting the access amount of the main client in a preset time period, and judging whether the access amount is greater than a preset threshold value;
and when the access amount is determined to be larger than the preset threshold value, extracting the access behavior characteristics of the access main client, matching the access behavior characteristics with the abnormal access behavior characteristics, and determining whether the access behavior characteristics of the access main client are the abnormal access behavior characteristics or not according to the matching result.
The working principle of the technical scheme is as follows: setting a main client, wherein the main client comprises a plurality of data sharing channels; detecting the access amount of the main client in a preset time period, and judging whether the access amount is greater than a preset threshold value; and when the access amount is determined to be larger than the preset threshold value, extracting the access behavior characteristics of the access main client, matching the access behavior characteristics with the abnormal access behavior characteristics, and determining whether the access behavior characteristics of the access main client are the abnormal access behavior characteristics or not according to the matching result.
The beneficial effects of the above technical scheme are that: the abnormal access behavior can be accurately detected, and corresponding measures are taken to ensure the security of data sharing.
According to some embodiments of the invention, further comprising: a third determination module for
After receiving the request data, the second client converts the request data into a target text and performs word segmentation to obtain a word segmentation set;
carrying out numerical processing on each participle in the participle set to determine an analytic numerical sequence;
determining a target number sequence of the request data before transmission;
and comparing the target digital sequence with the analysis numerical sequence, and determining abnormal information according to the comparison result.
The working principle of the technical scheme is as follows: the third determining module is used for converting the request data into a target text and performing word segmentation after the second client receives the request data to obtain a word segmentation set; carrying out numerical processing on each participle in the participle set to determine an analytic numerical sequence; determining a target number sequence of the request data before transmission; and comparing the target digital sequence with the analysis numerical sequence, and determining abnormal information according to the comparison result.
The beneficial effects of the above technical scheme are that: whether the data received by the second client is consistent with the data transmitted by the first client is accurately detected, and when the data is determined to be inconsistent, the abnormal information is determined, so that whether the data transmission is successful can be accurately detected, and then corresponding measures are taken, the consistency of the transmitted data and the received data is ensured, and the reliability of the data transmission is improved.
According to some embodiments of the invention, the encryption module comprises:
the generating submodule is used for randomly generating an encrypted character string according to a Random function;
and the encryption submodule is used for encrypting the request data according to the encryption character string.
The beneficial effects of the above technical scheme are that: the safety of data transmission is improved.
In one embodiment, the method further comprises:
the classification module is used for analyzing and classifying a plurality of sub-data included in the request data to obtain a plurality of classification sets before the second determination module sends the request data corresponding to the data request information to the first client based on the data sharing channel;
acquiring the types of the classification sets, inquiring a preset class priority sending data table, and determining the priority information of a plurality of classification sets;
and the second determining module sends the classification sets according to the priority information.
The working principle and the beneficial effects of the technical scheme are as follows: the classification module is used for analyzing and classifying a plurality of sub-data included in the request data to obtain a plurality of classification sets before the second determination module sends the request data corresponding to the data request information to the first client based on the data sharing channel; acquiring the types of the classification sets, inquiring a preset class priority sending data table, and determining the priority information of a plurality of classification sets; and the second determining module sends the classification sets according to the priority information. The integration of the same type of data is realized, the accurate data classification is convenient to realize, the management efficiency and the transmission efficiency of the data are improved, different sending priorities are set for different types of data, the priority sending of important type data is guaranteed, and the safety of the data is improved.
Analyzing and classifying a plurality of sub-data included in the request data to obtain a plurality of classification sets, including:
acquiring index information of a plurality of pieces of sub-data, and carrying out numerical processing on the index information to obtain an index numerical value; the index information comprises data keywords, data size, data sensitivity, data type and data source address;
randomly selecting two subdata, and calculating the probability that the two subdata are of the same type:
Figure BDA0003524556670000141
wherein, Pi,jIs the ith sub numberAccording to the probability of being the same as the jth sub-data; t isi,aThe a index value of the ith sub data; t isj,aThe a index value of the jth sub data; max (T)a) The maximum value of the a-th index value in the plurality of sub data is obtained; a is 1, 2, 3, 4, 5; the 1 st index value is a numerical processing result of the data keyword; the 2 nd index value is a numerical processing result of the data size; the 3 rd index value is a numerical processing result of the sensitivity to the data; the 4 th index value is a numerical processing result of the type of the data; the 5 th index value is a numerical processing result of a source address of the data;
taking the first subdata in the plurality of subdata as a category, calculating the probability that other subdata except the first subdata in the plurality of subdata and the first subdata are of the same type, respectively comparing the probabilities with a preset probability, and classifying the subdata with the probability greater than or equal to the preset probability to the category of the first subdata; and taking the subdata with the probability smaller than the preset probability as a group to be classified, selecting the first subdata of the group to be classified as a category, and repeating the steps until all the subdata are classified.
The working principle and the beneficial effects of the technical scheme are as follows: based on the formula, the probability that the two subdata data are of the same type is accurately calculated, so that the accuracy of determining the probability and the preset probability is improved, the subdata data are accurately classified, and the classification accuracy is improved.
In one embodiment, the method further comprises:
the supplier module is used for receiving the association data and screening out a target supplier according to the association data;
a quotation module to:
receiving quotation information sent by the target supplier, carrying out comprehensive analysis on the quotation information to obtain an analysis result, generating a new quotation according to the analysis result and sending the new quotation to a client;
and receiving confirmation information of the customer on the new price report, and generating order information according to the confirmation information.
The beneficial effects of the above technical scheme are that: the method and the system facilitate the determination of the correlation data of the customer according to the big data analysis technology, and screen out the target suppliers according to the correlation data, namely determining the suppliers related to the industry and business of the customer. The efficiency of screening suppliers is improved. And receiving the quotation information sent by the target supplier, carrying out comprehensive analysis on the quotation information to obtain an analysis result, generating a new quotation sheet according to the analysis result and sending the new quotation sheet to the client, so that the quotation of the target supplier can be conveniently screened and analyzed, a quotation scheme which is more favorable for the client in the market, namely the new quotation sheet, is obtained, and the new quotation sheet is sent to the client. The order information is generated based on the quotation of the target supplier and the confirmation information of the client on the quotation, so that the auditing and passing efficiency of the client on new quotation is improved, the generation of the order is accelerated, the service processing efficiency is improved, and the service requirement of the client is met.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims (10)

1. A customer intelligent management platform based on big data analysis technology is characterized by comprising:
the acquisition module is used for acquiring the login information of the client and carrying out verification processing:
the first determining module is used for checking the valid duration voucher of the client when the validation passes, and determining the login state of the client according to the expiration time of the valid duration voucher;
the establishing module is used for acquiring the business data of the client in the login process and marking the industry type of the client; collecting a target data source according to the industry type of a client, and establishing a big data directory according to the target data source;
the matching module is used for matching the service data with the big data directory to determine matching data;
and the second determining module is used for determining the associated data related to the matched data in the big data directory and pushing the associated data to the client.
2. The big data analytics technology-based customer intelligent management platform of claim 1, wherein the login information includes a user name and a user password.
3. The big data analytics technology-based customer intelligent management platform as claimed in claim 1, further comprising a build module for
Acquiring historical application data of a client;
performing data analysis on the historical application data, determining scene data and content data, dividing the scene data based on a preset scene category, and determining the scene data into a plurality of scene nodes;
acquiring the node levels of the scene nodes, and determining the connection relation among the scene nodes according to the node levels;
filling the content data to corresponding scene nodes, and constructing a scene tree according to the connection relation;
extracting the characteristics of the content data in each scene node in the scene tree, and determining client labels in different scenes;
and respectively constructing customer images of different scenes according to the customer labels in the different scenes.
4. The big data analytics technology-based customer intelligent management platform of claim 1, further comprising: detection module for
Acquiring current application data of a client;
analyzing the current application data, and determining a current scene and current content;
extracting the characteristics of the current content, and determining a temporary label in the current scene;
constructing a temporary customer portrait of the current scene according to the temporary label;
calculating the matching degree of the temporary customer portrait and the customer portrait corresponding to the current scene, and judging whether the matching degree is greater than a preset matching degree;
when the matching degree is smaller than a preset matching degree, analyzing the current content, determining a customer behavior, and decomposing the customer behavior into a plurality of sub behaviors;
establishing a queuing queue according to the plurality of sub-behaviors, and determining every two adjacent sub-behaviors in the queuing queue as a group as a detection group;
respectively calculating the association degrees between two sub-behaviors in the detection group, and screening out the detection group with the association degree smaller than the preset association degree as a marker group;
respectively judging whether the two sub-behaviors in the mark group are complete behaviors, and sending an alarm prompt when the mark group with the two sub-behaviors which are not complete behaviors is determined to exist;
otherwise, the client portrait corresponding to the current scene is updated according to the temporary client portrait.
5. The big data analytics technology-based customer intelligent management platform of claim 1, further comprising: shared module for
Receiving data request information of a first client and sending the data request information to a second client;
receiving feedback information of a second client, and establishing a data sharing channel between the first client and the second client according to the feedback information;
and sending request data corresponding to the data request information to the first client based on the data sharing channel.
6. The big data analytics technology-based customer intelligent management platform of claim 5, further comprising: and the encryption module is used for encrypting the request data corresponding to the data request information before sending the request data to the first client based on the data sharing channel.
7. The big data analytics technology-based customer intelligent management platform as claimed in claim 5, further comprising a prediction module for
Detecting whether an attack event exists or not in the process of sending request data by the sharing module;
when an attack event is determined to occur, determining an attack sequence diagram;
inputting the attack sequence diagram into a pre-trained prediction model to determine prediction information;
and determining a protective measure for the attack node according to the prediction information.
8. The big data analytics technology-based customer intelligent management platform of claim 1, further comprising:
setting a main client, wherein the main client comprises a plurality of data sharing channels;
detecting the access amount to the main client in a preset time period, and judging whether the access amount is greater than a preset threshold value;
and when the access amount is determined to be larger than the preset threshold value, extracting the access behavior characteristics of the access master client, matching the access behavior characteristics with the abnormal access behavior characteristics, and determining whether the access behavior characteristics of the access master client are the abnormal access behavior characteristics or not according to a matching result.
9. The big data analytics technology-based customer intelligent management platform of claim 5, further comprising: a third determination module for
After receiving the request data, the second client converts the request data into a target text and performs word segmentation to obtain a word segmentation set;
carrying out numerical processing on each participle in the participle set to determine an analytic numerical sequence;
determining a target number sequence of the request data before transmission;
and comparing the target digital sequence with the analysis numerical sequence, and determining abnormal information according to the comparison result.
10. The big data analytics technology-based customer intelligent management platform of claim 1, further comprising:
the supplier module is used for receiving the associated data and screening out a target supplier according to the associated data;
a quotation module to:
receiving quotation information sent by the target supplier, carrying out comprehensive analysis on the quotation information to obtain an analysis result, generating a new quotation according to the analysis result and sending the new quotation to a client;
and receiving confirmation information of the customer on the new price report, and generating order information according to the confirmation information.
CN202210188369.4A 2022-02-28 2022-02-28 Customer intelligent management platform based on big data analysis technology Pending CN114565435A (en)

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CN202210188369.4A CN114565435A (en) 2022-02-28 2022-02-28 Customer intelligent management platform based on big data analysis technology

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210188369.4A CN114565435A (en) 2022-02-28 2022-02-28 Customer intelligent management platform based on big data analysis technology

Publications (1)

Publication Number Publication Date
CN114565435A true CN114565435A (en) 2022-05-31

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Application Number Title Priority Date Filing Date
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